OpenChess-Insights
TensorFlow-Examples
OpenChess-Insights | TensorFlow-Examples | |
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2 | 2 | |
33 | 43,246 | |
- | - | |
6.9 | 0.0 | |
5 months ago | 7 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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OpenChess-Insights
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I made myself a free version of chess.com's game review!
Here's the project page https://github.com/LinkAnJarad/OpenChess-Insights
TensorFlow-Examples
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Keras vs. TensorFlow
A linear regression model
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Tensorman and RTX 30-Series GPU's
When I run this simple project, the log output is below. There is a 5-minute pause at 16:48. There is a second pause at the end of the script before the output of the example (final output excluded). This project runs quickly if I exclude "--gpu" and run it on the CPU.
What are some alternatives?
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
graphkit-learn - A python package for graph kernels, graph edit distances, and graph pre-image problem.
pyVHR - Python framework for Virtual Heart Rate
TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos
Deep-Learning-Hardware-Benchmark - This repository contains the proposed implementation for benchmarking in order to evaluate whether a setup of hardware is feasible for deep learning projects.
rmi - A learned index structure
Deep-Learning-With-TensorFlow-Blog-series - All the resources and hands-on exercises for you to get started with Deep Learning in TensorFlow [Moved to: https://github.com/Rishit-dagli/Deep-Learning-With-TensorFlow]
TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!
models - A collection of pre-trained, state-of-the-art models in the ONNX format
single-parameter-fit - Real numbers, data science and chaos: How to fit any dataset with a single parameter
car-damage-detection - Detectron2 for car damage detection using custom dataset
entity-embed - PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.